Self-adaptation in Collective Self-aware Computing Systems

Self-Aware Computing Systems

Volumn , Issue , 2017, Pages 401-435

  Kephart, Jeffrey O ^a   Diaconescu, Ada ^b   Giese, Holger ^c   Robertsson, Anders ^d   Abdelzaher, Tarek ^e   Lewis, Peter ^f   Filieri, Antonio ^g   Esterle, Lukas ^h   Frey, Sylvain ⁱ  

^a IBM T J WATSON RESEARCH CENTER   (United States)

^b UNIVERSITÉ PARIS SACLAY   (France)

^c UNIVERSITY OF POTSDAM   (Germany)

^d LUND UNIVERSITY   (Sweden)

^e University of Illinois at Urbana Champaign   (United States)

^f ASTON UNIVERSITY   (United Kingdom)

^g IMPERIAL COLLEGE LONDON   (United Kingdom)

^h VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

ⁱ LANCASTER UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85047270631     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-319-47474-8_13     Document Type: Chapter

References (39)

1. Jacob Beal, Jeffrey Berliner, and Kevin Hunter. Fast precise distributed control for energy demand management. In Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on, pages 187-192. IEEE, 2012
2. Basil Becker, Dirk Beyer, Holger Giese, Florian Klein, and Daniela Schilling. Symbolic Invariant Verification for Systems with Dynamic Structural Adaptation. In Proc. of the 28th International Conference on Software Engineering (ICSE), Shanghai, China. ACM Press, 2006
3. Sven Burmester, Holger Giese, Eckehard Mnch, Oliver Oberschelp, Florian Klein, and Peter Scheideler. Tool Support for theDesign of Self-OptimizingMechatronic Multi-Agent Systems. International Journal on Software Tools for Technology Transfer (STTT), 10(3):207-222, June 2008
4. Lucian Busoniu, Robert Babuska, and Bart De Schutter. A comprehensive survey of multiagent reinforcement learning. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 38(2):156-172, 2008
5. Caroline Claus and Craig Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National/Tenth Conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, AAAI '98/IAAI '98, pages 746-752, Menlo Park, CA, USA, 1998. American Association for Artificial Intelligence
6. Vincent Conitzer and Tuomas Sandholm. Self-interested automated mechanism design and implications for optimal combinatorial auctions. In Proceedings of the 5th ACM conference on Electronic commerce, pages 132-141. ACM, 2004
7. Constantinos Daskalakis, PaulWGoldberg, and Christos H Papadimitriou. The complexity of computing a Nash equilibrium. SIAM Journal on Computing, 39(1):195-259, 2009
8. Ada Diaconescu and Jeremy Pitt. Coordination, Organizations, Institutions, and Norms in Agent Systems X, volume 9372 of Lecture Notes in Artificial Intelligence, chapter Holonic Institutions for Multi-scale Polycentric Self-governance, pages 19-35. Springer International Publishing, 1 edition, 2015
9. JoseLuis Fernandez-Marquez, Giovanna Di Marzo Serugendo, Sara Montagna, Mirko Viroli, and JosepLluis Arcos. Description and Composition of Bio-inspired Design Patterns: a Complete Overview. Natural Computing, 12(1):43-67, 2013
10. Dean P Foster and Rakesh V Vohra. Calibrated learning and correlated equilibrium. Games and Economic Behavior, 21(1):40-55, 1997
11. Sylvain Frey, AdaDiaconescu, DavidMenga, and Isabelle Demeure.Aholonic control architecture for a heterogeneous multi-objective smart micro-grid. In Self-Adaptive and Self-Organizing Systems (SASO), 2013 IEEE 7th International Conference on, pages 21-30. IEEE, 2013
12. Sylvain Frey, François Huguet, Cédric Mivielle, David Menga, AdaDiaconescu, and IsabelleM Demeure. Scenarios for an autonomic micro smart grid. In SMARTGREENS, pages 137-140, 2012
13. Theodore Geisel. The Cat in the Hat Comes Back. Random House, 1958
14. Holger Giese, Sven Burmester, Florian Klein, Daniela Schilling, and Matthias Tichy. Multi-Agent System Design for Safety-Critical Self-Optimizing Mechatronic Systems with UML. In Brian Henderson-Sellers and J Debenham, editors, OOPSLA 2003-Second International Workshop on Agent-Oriented Methodologies, pages 21-32, Anaheim, CA, USA, Center for Object Technology Applications and Research (COTAR), University of Technology, Sydney, Australia, October 2003
15. Holger Giese and Wilhelm Schäfer. Model-Driven Development of Safe Self-Optimizing Mechatronic Systems with MechatronicUML. In Javier Camara, Rogrio de Lemos, Carlo Ghezzi, and Antânia Lopes, editors, Assurances for Self-Adaptive Systems, volume 7740 of Lecture Notes in Computer Science (LNCS), pages 152-186. Springer, January 2013
16. Harry Goldingay and Peter R. Lewis. A Taxonomy of Heterogeneity and Dynamics in Particle SwarmOptimisation. In Thomas Bartz-Beielstein, Jrgen Branke, Bogdan Filipi, and Jim Smith, editors, Parallel Problem Solving from Nature PPSN XIII, volume 8672 of Lecture Notes in Computer Science, pages 171-180. Springer International Publishing, 2014
17. Amy R Greenwald and Jeffrey O Kephart. Probabilistic pricebots. In Proceedings of the fifth international conference on Autonomous agents, pages 560-567. ACM, 2001
18. James E Hanson, Gerald J. Tesauro, Jeffrey O Kephart, and Edward C Snible. Multi-agent implementation of asymmetric protocol for bilateral negotiations. In Proceedings of the 4th ACM Conference on Electronic Commerce, pages 224-225. ACM, 2003
19. Sergiu Hart and Andreu Mas-Colell. A simple adaptive procedure leading to correlated equilibrium. Econometrica, 68(5):1127-1150, 2000
20. Jin Heo and Tarek F. Abdelzaher. Adaptguard: guarding adaptive systems from instability. In Simon A. Dobson, John Strassner, Manish Parashar, and Onn Shehory, editors, Proceedings of the 6th International Conference on Autonomic Computing, ICAC 2009, June 15-19, 2009, Barcelona, Spain, pages 77-86. ACM, 2009
21. Amir Jafari, Amy Greenwald, David Gondek, andGunes Ercal.On no-regret learning, fictitious play, and nash equilibrium. In In Proceedings of the Eighteenth International Conference on Machine Learning, 2001
22. J O Kephart, H Chan, R Das, D W Levine, G Tesauro, and C Lefurgy. Coordinating multiple autonomic managers to achieve specified power-performance tradeoffs. In Proceedings of the Fourth International Conference on Autonomic Computing. IEEE, 2007
23. Jeffrey O Kephart. Can predictive agents prevent chaos. Economics and cognitive science
24. Jeffrey O Kephart. Software agents and the route to the information economy. Proceedings of the National Academy of Sciences, 99(suppl 3):7207-7213, 2002
25. Jeffrey O Kephart and David M Chess. The vision of autonomic computing. Computer, 36(1):41-50, 2003
26. Jeffrey. O.Kephart, Tad Hogg, andBernardoA.Huberman.Dynamics of computational ecosystems. Phys. Rev. A, 40:404-421, Jul 1989
27. Jeffrey O Kephart, Tad Hogg, and Bernardo A Huberman. Collective behavior of predictive agents. Physica D: Nonlinear Phenomena, 42(1):48-65, 1990
28. Jeffrey O Kephart and Jonathan Lenchner. A symbiotic cognitive computing perspective on autonomic computing. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing. IEEE, 2015
29. Jeffrey O Kephart and Gerald J Tesauro. Pseudo-convergent q-learning by competitive pricebots. In Proc. 17th Intl Conf. Machine Learning, pages 463-470, 2000
30. Jeffrey O Kephart and William E Walsh. An artificial intelligence perspective on autonomic computing policies. In Policies for Distributed Systems and Networks, 2004. POLICY 2004. Proceedings. Fifth IEEE International Workshop on, pages 3-12. IEEE, 2004
31. Peter R. Lewis, Arjun Chandra, Funmilade Faniyi, Kyrre Glette, Tao Chen, Rami Bahsoon, Jim Torresen, and Xin Yao. Architectural Aspects of Self-Aware and Self-Expressive Systems: From Psychology to Engineering. Computer, 48(8), August 2015
32. Peter R. Lewis, Paul Marrow, and Xin Yao. Resource Allocation in Decentralised Computational Systems:AnEvolutionary Market BasedApproach.Autonomous Agents and Multi-Agent Systems, 21(2):143-171, 2010
33. Fernando Perez-Diaz, Ruediger Zillmer, and Roderich Groß. Firefly-inspired synchronization in swarms of mobile agents. In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS '15, pages 279-286, Richland, SC, 2015. International Foundation for Autonomous Agents and Multiagent Systems
34. Ramya Raghavendra, Parthasarathy Ranganathan, Vanish Talwar, Zhikui Wang, and Xiaoyun Zhu. No power struggles: Coordinated multi-level power management for the data center. In ACM SIGARCH Computer Architecture News, volume 36, pages 48-59. ACM, 2008
35. Tuomas Sandholm. Algorithm for optimal winner determination in combinatorial auctions. Artificial intelligence, 135(1):1-54, 2002
36. H.VanDyke Parunak, Sven Brueckner, Mitch Fleischer, and JamesOdell.ADesign Taxonomy of Multi-agent Interactions. In Paolo Giorgini, JrgP. Mller, and James Odell, editors, Agent-Oriented Software Engineering IV, volume 2935 of Lecture Notes in Computer Science, pages 123-137. Springer Berlin Heidelberg, 2004
37. William Vickrey. Counterspeculation, auctions, and competitive sealed tenders. The Journal of finance, 16(1):8-37, 1961
38. William E Walsh, Gerald Tesauro, Jeffrey O Kephart, and Rajarshi Das. Utility functions in autonomic systems. In Autonomic Computing, 2004. Proceedings. International Conference on, pages 70-77. IEEE, 2004
39. M P Wellman, W E Walsh, P R Wurman, and J K MacKie-Mason. Auction protocols for decentralized scheduling. Games and economic behavior, 35(1):271-303, 2001